Array programming with NumPy
Charles R. Harris,K. Jarrod Millman,Stefan van der Walt,Stefan van der Walt,Ralf Gommers,Pauli Virtanen,David Cournapeau,Eric Wieser,Julian Taylor,Sebastian Berg,Nathaniel J. Smith,Robert Kern,Matti Picus,Stephan Hoyer,Marten H. van Kerkwijk,Matthew Brett,Matthew Brett,Allan Haldane,Jaime Fernández del Río,Mark Wiebe,Mark Wiebe,Pearu Peterson,Pierre Gérard-Marchant,Kevin Sheppard,Tyler Reddy,Warren Weckesser,Hameer Abbasi,Christoph Gohlke,Travis E. Oliphant +28 more
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In this paper, the authors review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data, and their evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.Abstract:
Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis. NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.read more
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A new test of the Cosmological Principle: measuring our peculiar velocity and the large scale anisotropy independently
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Molecules with ALMA at Planet-forming Scales (MAPS). IX. Distribution and Properties of the Large Organic Molecules HC 3 N, CH 3 CN, and c-C 3 H 2
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Feedback from nuclear RNA on transcription promotes robust RNA concentration homeostasis in human cells.
TL;DR: In this article , the authors study the effect of genome-wide perturbations on RNA synthesis and find that RNA concentrations generally remain highly constant in human cells, despite relative ease in perturbing RNA synthesis.
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The NANOGrav 15 yr Data Set: Observations and Timing of 68 Millisecond Pulsars
G. Y. Agazie,Md F. Alam,A. Anumarlapudi,Anne M. Archibald,Zaven Arzoumanian,P. T. Baker,Laura Blecha,Victoria Bonidie,Adam Brazier,Paul R. Brook,Sarah Burke-Spolaor,B. B'ecsy,Maria Charisi,Shami Chatterjee,Tyler Cohen,James M. Cordes,Neil J. Cornish,Fronefield Crawford,H. Thankful Cromartie,Kathryn Crowter,Megan E. DeCesar,Paul Demorest,Timothy Dolch,Brendan Drachler,V. Ferrara,William Fiore,Emmanuel Fonseca,Gabrielle Freedman,N. Garver-Daniels,Peter A. Gentile,Joseph P Glaser,Deborah C. Good,K. Gultekin,Jeffrey S. Hazboun,Ross J. Jennings,Cody Jessup,Aaron M. Johnson,Megan L. Jones,Andrew R. Kaiser,David L. Kaplan,Luke Zoltan Kelley,Matthew Kerr,Joey Shapiro Key,A. Kuske,Nima Laal,Michael T. Lam,W. Lamb,T. J. W. Lazio,Natalia Lewandowska,Tianyu Liu,Duncan R. Lorimer,Jingtao Luo,Ryan Lynch,Chung-Pei Ma,D. R. Madison,Kaleb Maraccini,Alexander McEwen,J. W. McKee,Maura McLaughlin,Natasha McMann,B. W. Meyers,Chiara M. F. Mingarelli,Andrea Mitridate,Cherry Ng,David J. Nice,S. Ocker,Ken D. Olum,Timothy T. Pennucci,Benetge Perera,Nihan Pol,Henri A. Radovan,Scott M. Ransom,Paul S. Ray,Joseph D. Romano,Laura Salo,Shashwat C. Sardesai,C. Schmiedekamp,Ann B. Schmiedekamp,M. Schmitz,Brent J. Shapiro-Albert,Xavier Siemens,Joseph Simon,Magdalena Siwek,Ingrid H. Stairs,Daniel R. Stinebring,Kevin Stovall,Abhimanyu Susobhanan,Joseph K. Swiggum,Stephen Taylor,J. E. Turner,Caner Unal,Michele Vallisneri,Sarah J. Vigeland,Haley M. Wahl,Qiaohong Wang,Caitlin A. Witt,Olivia Young +96 more
TL;DR: In this paper , the authors present observations and timing analyses of 68 millisecond pulsars (MSPs) comprising the 15 yr data set of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav).
References
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Journal Article
Scikit-learn: Machine Learning in Python
Fabian Pedregosa,Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,Bertrand Thirion,Olivier Grisel,Mathieu Blondel,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Brucher,Matthieu Perrot,Edouard Duchesnay +15 more
TL;DR: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems, focusing on bringing machine learning to non-specialists using a general-purpose high-level language.
Posted Content
Scikit-learn: Machine Learning in Python
Fabian Pedregosa,Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,Bertrand Thirion,Olivier Grisel,Mathieu Blondel,Andreas Müller,Joel Nothman,Gilles Louppe,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Brucher,Matthieu Perrot,Edouard Duchesnay +18 more
TL;DR: Scikit-learn as mentioned in this paper is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.
Journal ArticleDOI
Matplotlib: A 2D Graphics Environment
TL;DR: Matplotlib is a 2D graphics package used for Python for application development, interactive scripting, and publication-quality image generation across user interfaces and operating systems.
Journal ArticleDOI
SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
Pauli Virtanen,Ralf Gommers,Travis E. Oliphant,Matt Haberland,Matt Haberland,Tyler Reddy,David Cournapeau,Evgeni Burovski,Pearu Peterson,Warren Weckesser,Jonathan Bright,Stefan van der Walt,Matthew Brett,Joshua Wilson,K. Jarrod Millman,Nikolay Mayorov,Andrew Nelson,Eric Jones,Robert Kern,Eric B. Larson,CJ Carey,Ilhan Polat,Yu Feng,Eric Moore,Jake Vanderplas,Denis Laxalde,Josef Perktold,Robert Cimrman,Ian Henriksen,Ian Henriksen,E. A. Quintero,Charles R. Harris,Anne M. Archibald,Antônio H. Ribeiro,Fabian Pedregosa,Paul van Mulbregt,SciPy . Contributors +36 more
TL;DR: SciPy as discussed by the authors is an open source scientific computing library for the Python programming language, which includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics.
Proceedings ArticleDOI
TensorFlow: a system for large-scale machine learning
Martín Abadi,Paul Barham,Jianmin Chen,Zhifeng Chen,Andy Davis,Jeffrey Dean,Matthieu Devin,Sanjay Ghemawat,Geoffrey Irving,Michael Isard,Manjunath Kudlur,Josh Levenberg,Rajat Monga,Sherry Moore,Derek G. Murray,Benoit Steiner,Paul A. Tucker,Vijay K. Vasudevan,Pete Warden,Martin Wicke,Yuan Yu,Xiaoqiang Zheng +21 more
TL;DR: TensorFlow as mentioned in this paper is a machine learning system that operates at large scale and in heterogeneous environments, using dataflow graphs to represent computation, shared state, and the operations that mutate that state.
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